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Customer Lifetime Value : An Integrated Data Mining Approach, Chen Xu Aug 2006

Customer Lifetime Value : An Integrated Data Mining Approach, Chen Xu

Lingnan Theses

Customer Lifetime Value (CLV) ---which is a measure of the profit generating potential, or value, of a customer---is increasingly being considered a touchstone for customer relationship management. As the guide and benchmark for Customer Relationship Management (CRM) applications, CLV analysis has received increasing attention from both the marketing practitioners and researchers from different domains. Furthermore, the central challenge in predicting CLV is the precise calculation of customer’s length of service (LOS). There are several statistical approaches for this problem and several researchers have used these approaches to perform survival analysis in different domains. However, classical survival analysis techniques like Kaplan-Meier …

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Improved Generalized Estimating Equation Analysis Via Xtqls For Implementation Of Quasi-Least Squares In Stata, Justine Shults, Sarah J. Ratcliffe, Mary Leonard Aug 2006

Improved Generalized Estimating Equation Analysis Via Xtqls For Implementation Of Quasi-Least Squares In Stata, Justine Shults, Sarah J. Ratcliffe, Mary Leonard

UPenn Biostatistics Working Papers

No abstract provided.

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Adjustment Uncertainty In Effect Estimation, Ciprian M. Crainiceanu, Francesca Dominici, Giovanni Parmigiani Aug 2006

Adjustment Uncertainty In Effect Estimation, Ciprian M. Crainiceanu, Francesca Dominici, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

The selection of confounders and their functional relationship with the out- come affects exposure effect estimates. In practice, there is often substantial uncertainty about this selection, which we define here as “adjustment uncertainty.” We address the problem of estimating the effect of exposure on an outcome with focus on quantifying the effect of unknown confounders from a large set of potential confounders. We propose a general statistical framework for handling adjustment uncertainty in exposure effect estimation, a specific implementation called "Structured Estimation under Adjustment Uncertainty (STEADy)", and associated visualization tools. Theoretical results and simulation studies show that STEADy consistently estimates …

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A Flexible Statistical Method For Detecting Genomic Copy-Number Changes Using Hidden Markov Models With Reversible Jump Mcmc , Oscar M. Rueda, Ramon Diaz-Uriarte Aug 2006

A Flexible Statistical Method For Detecting Genomic Copy-Number Changes Using Hidden Markov Models With Reversible Jump Mcmc , Oscar M. Rueda, Ramon Diaz-Uriarte

COBRA Preprint Series

We have developed a statistical method for the analysis of array based CGH data to detect genomic DNA copy number changes. Our method allows us to answer the biologically relevant questions (what is the probability that a given gene or region has increased or decreased copy number changes) in a clear and simple way, within a rigorous statistical framework. We use a non-homogeneous Hidden Markov Model that incorporates distance between genes, a crucial requirement to analyze data from platforms where distances between probes is highly variable. As the true number of hidden states (states of copy number changes) is not …

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Simultaneously Optimizing Dose And Schedule Of A New Cytotoxic Agent, Thomas M. Braun, Peter F. Thall, Hoang Nguyen, Marcos De Lima Aug 2006

Simultaneously Optimizing Dose And Schedule Of A New Cytotoxic Agent, Thomas M. Braun, Peter F. Thall, Hoang Nguyen, Marcos De Lima

The University of Michigan Department of Biostatistics Working Paper Series

Traditionally, phase I clinical trial designs determine a maximum tolerated dose of an experimental cytotoxic agent based on a fixed schedule, usually one course consisting of multiple administrations, while varying the dose per administration between patients. However, in actual medical practice patients often receive several courses of treatment, and some patients may receive one or more dose reductions due to low-grade (non-dose limiting) toxicity in previous courses. As a result, the overall risk of toxicity for each patient is a function of both the schedule and the dose used at each adminstration. We propose a new paradigm for Phase I …

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Additional Algorithms For Sensor Chip Alignment To Blind Datums, Gary B. Hughes Aug 2006

Additional Algorithms For Sensor Chip Alignment To Blind Datums, Gary B. Hughes

Statistics

Alignment of the sensor focal plane array (FPA) to optical components is a critical design feature. Imaging system designs include reference datums that provide the basis for manufacturing alignment in each sub-assembly. Measurement of z and parallelism positioning can be problematic, since the relevant datum features are often beneath the mounting platform and are obscured to the measurement system. General algorithms for determining sensor chip alignment when datum features are inaccessible to the measurement system have been developed. Pre-characterization measurements of datum surfaces are stored for later use during alignment measurement to determine datum locations. The algorithms are useful for …

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Amended Estimators Of Several Ratios For Categorical Data., Dandan Chen Aug 2006

Amended Estimators Of Several Ratios For Categorical Data., Dandan Chen

Electronic Theses and Dissertations

Point estimation of several association parameters in categorical data are presented. Typically, a constant is added to the frequency counts before the association measure is computed. We will study the accuracy of these adjusted point estimators based on frequentist and Bayesian methods respectively. In particular, amended estimators for the ratio of independent Poisson rates, relative risk, odds ratio, and the ratio of marginal binomial proportions will be examined in terms of bias and mean squared error.

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Comparing The Statistical Tests For Homogeneity Of Variances., Zhiqiang Mu Aug 2006

Comparing The Statistical Tests For Homogeneity Of Variances., Zhiqiang Mu

Electronic Theses and Dissertations

Testing the homogeneity of variances is an important problem in many applications since statistical methods of frequent use, such as ANOVA, assume equal variances for two or more groups of data. However, testing the equality of variances is a difficult problem due to the fact that many of the tests are not robust against non-normality. It is known that the kurtosis of the distribution of the source data can affect the performance of the tests for variance. We review the classical tests and their latest, more robust modifications, some other tests that have recently appeared in the literature, and use …

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Generalized Monotonic Functional Mixed Models With Application To Modeling Normal Tissue Complications , Matthew Schipper, Jeremy Taylor, Xihong Lin Aug 2006

Generalized Monotonic Functional Mixed Models With Application To Modeling Normal Tissue Complications , Matthew Schipper, Jeremy Taylor, Xihong Lin

The University of Michigan Department of Biostatistics Working Paper Series

Normal tissue complications are a common side effect of radiation therapy. They are the consequence of the dose of radiation received by the normal tissue surrounding the tumor site. It is not known what function of the dose distribution to the normal tissue drives the presence and severity of the complications. Regarding the density of the dose distribution as a curve, a summary measure is obtained by integrating a weighting function of dose (w(d)) over the dose density. For biological reasons the weight function should be monotonic. We propose to study the dose effect on a clinical outcome using a …

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Sources Of Variability In A Proteomic Experiment, Scott Daniel Crawford Aug 2006

Sources Of Variability In A Proteomic Experiment, Scott Daniel Crawford

Theses and Dissertations

The study of proteomics holds the hope for detecting serious diseases earlier than is currently possible by analyzing blood samples in a mass spectrometer. Unfortunately, the statistics involved in comparing a control group to a diseased group are not trivial, and these difficulties have led others to incorrect decisions in the past. This paper considers a nested design that was used to quantify and identify the sources of variation in the mass spectrometer at BYU, so that correct conclusions can be drawn from blood samples analyzed in proteomics. Algorithms were developed which detect, align, correct, and cluster the peaks in …

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Bayesian Smoothing Of Irregularly-Spaced Data Using Fourier Basis Functions, Christopher J. Paciorek Aug 2006

Bayesian Smoothing Of Irregularly-Spaced Data Using Fourier Basis Functions, Christopher J. Paciorek

Harvard University Biostatistics Working Paper Series

No abstract provided.

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Predicting Future Responses Based On Possibly Misspecified Working Models, Tianxi Cai, Lu Tian, Scott D. Solomon, L.J. Wei Aug 2006

Predicting Future Responses Based On Possibly Misspecified Working Models, Tianxi Cai, Lu Tian, Scott D. Solomon, L.J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

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Nested Markov Compliance Class Model In The Presence Of Time-Varying Noncompliance, Julia Y. Lin, Thomas R. Tenhave, Michael R. Elliott Aug 2006

Nested Markov Compliance Class Model In The Presence Of Time-Varying Noncompliance, Julia Y. Lin, Thomas R. Tenhave, Michael R. Elliott

UPenn Biostatistics Working Papers

We consider a Markov structure for partially unobserved time-varying compliance classes in the Imbens-Rubin (1997) compliance model framework. The context is a longitudinal randomized intervention study where subjects are randomized once at baseline, outcomes and patient adherence are measured at multiple follow-ups, and patient adherence to their randomized treatment could vary over time. We propose a nested latent compliance class model where we use time-invariant subject-specific compliance principal strata to summarize longtudinal trends of subject-specific time-varying compliance patterns. The principal strata are formed using Markov models that related current compliance behavior to compliance history. Treatment effects are estimated as intent-to …

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Chainability And Hemmingsen's Theorem, Paul Bankston Aug 2006

Chainability And Hemmingsen's Theorem, Paul Bankston

Mathematics, Statistics and Computer Science Faculty Research and Publications

On the surface, the definitions of chainability and Lebesgue covering dimension ⩽1 are quite similar as covering properties. Using the ultracoproduct construction for compact Hausdorff spaces, we explore the assertion that the similarity is only skin deep. In the case of dimension, there is a theorem of E. Hemmingsen that gives us a first-order lattice-theoretic characterization. We show that no such characterization is possible for chainability, by proving that if κ is any infinite cardinal and AA is a lattice base for a nondegenerate continuum, then AA is elementarily equivalent to a lattice base for a continuum Y …

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Incentive Awards To Class Action Plaintiffs: An Empirical Study, Theodore Eisenberg, Geoffrey P. Miller Aug 2006

Incentive Awards To Class Action Plaintiffs: An Empirical Study, Theodore Eisenberg, Geoffrey P. Miller

Cornell Law Faculty Publications

Incentive awards to representative plaintiffs in class actions have been the focus of recent law reform efforts and have generated inconsistent case law. But little is known about such awards. This study of 374 opinions from 1993 to 2002 finds that awards were granted in about 28 percent of settled class actions. The rate of awards varied by case category as follows: consumer credit actions 59 percent, employment discrimination cases 46 percent, antitrust cases 35 percent, securities cases 24 percent (before the Private Securities Litigation Reform Act of 1995 limited awards), and corporate and mass tort actions less than 10 …

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An Informative Bayesian Structural Equation Model To Assess Source-Specific Health Effects Of Air Pollution, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski Jul 2006

An Informative Bayesian Structural Equation Model To Assess Source-Specific Health Effects Of Air Pollution, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski

Harvard University Biostatistics Working Paper Series

No abstract provided.

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Mixed Multiplicative Factor Analysis Model For Air Pollution Exposure Assessment, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski Jul 2006

Mixed Multiplicative Factor Analysis Model For Air Pollution Exposure Assessment, Margaret C. Nikolov, Brent A. Coull, Paul J. Catalano, John J. Godleski

Harvard University Biostatistics Working Paper Series

No abstract provided.

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Survival Analysis Of Longitudinal Microarrays, Natasa Rajicic, Dianne M. Finkelstein, David A. Schoenfeld Jul 2006

Survival Analysis Of Longitudinal Microarrays, Natasa Rajicic, Dianne M. Finkelstein, David A. Schoenfeld

COBRA Preprint Series

Motivation: The development of methods for linking gene expressions to various clinical and phenotypic characteristics is an active area of genomic research. Scientists hope that such analysis may, for example, describe relationships between gene function and clinical events such as death or recovery. Methods are available for relating gene expression to measurements that are categorized or continuous, but there is less work in relating expressions to an observed event time such as time to death, response, or relapse. When gene expressions are measured over time, there are methods for differentiating temporal patterns. However, no methods have yet been proposed for …

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Relative Risk Regression In Medical Research: Models, Contrasts, Estimators, And Algorithms, Thomas Lumley, Richard Kronmal, Shuangge Ma Jul 2006

Relative Risk Regression In Medical Research: Models, Contrasts, Estimators, And Algorithms, Thomas Lumley, Richard Kronmal, Shuangge Ma

UW Biostatistics Working Paper Series

The relative risk or prevalence ratio is a natural and familiar summary of association between a binary outcome and an exposure or intervention. For rare events, the relative risk can be approximately estimated by logistic regression. For common events estimation is more difficult. We review proposed estimation algorithms for relative risk regression. Some of these give inconsistent estimates or invalid standard errors. We show that the methods that give correct inference can be viewed as arising from a family of quasilikelihood estimating functions for the same generalized linear model, differing in their efficiency and in their robustness to outlying values …

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A Flexible General Class Of Marginal And Conditional Random Intercept Models For Binary Outcomes Using Mixtures Of Normals, Brian Caffo, Ming-Wen An, Charles A. Rohde Jul 2006

A Flexible General Class Of Marginal And Conditional Random Intercept Models For Binary Outcomes Using Mixtures Of Normals, Brian Caffo, Ming-Wen An, Charles A. Rohde

Johns Hopkins University, Dept. of Biostatistics Working Papers

Random intercept models for binary data are useful tools for addressing between subject heterogeneity. Unlike linear models, the non-linearity of link functions used for binary data force a distinction between marginal and conditional interpretations. This distinction is blurred in probit models with a normally distributed random intercept because the resulting model implies a probit marginal link as well. That is, this model is closed in the sense that the distribution associated with the marginal and conditional link functions and the random effect distribution are all of the same family. In this manuscript we explore another family of random intercept models …

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The Combination Of Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield Jul 2006

The Combination Of Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield

UW Biostatistics Working Paper Series

Ecological studies, in which data are available at the level of the group, rather than at the level of the individual, are susceptible to a range of biases due to their inability to characterize within-group variability in exposures and confounders. In order to overcome these biases, we propose a hybrid design in which ecological data are supplemented with a sample of individual-level case-control data. We develop the likelihood for this design and illustrate its benefits via simulation, both in bias reduction when compared to an ecological study, and in efficiency gains relative to a conventional case-control study. An interesting special …

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Understanding Brigham Young University's Technology Teacher Education Program's Sucess In Attracting And Retaining Female Students, Katrina M. Cox Jul 2006

Understanding Brigham Young University's Technology Teacher Education Program's Sucess In Attracting And Retaining Female Students, Katrina M. Cox

Theses and Dissertations

The purpose of the study was to attempt to understand why Brigham Young University Technology Teacher Education program has attracted and retained a high number of females. This was done through a self-created survey composed of four forced responses, distributed among the Winter 2006 semester students. Likert-scale questions were outlined according to the five theoretical influences on women in technology, as established by Welty and Puck (2001) and two of the three relationships of academia, as established by Haynie III (1999), as well as three free response questions regarding retention and attraction within the major. Findings suggested strong positive polarity …

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Permutation Methods In Relative Risk Regression Models, Wenyu Jiang, Jack Kalbfleisch Jul 2006

Permutation Methods In Relative Risk Regression Models, Wenyu Jiang, Jack Kalbfleisch

The University of Michigan Department of Biostatistics Working Paper Series

In this paper, we develop a weighted permutation (WP) method to construct confidence intervals for regression parameters in relative risk regression models. The WP method is a generalized permutation approach. It constructs a resampled history which mimics the observed history for individuals under study. Inference procedures are based on studentized score statistics that are insensitive to the forms of the relative risk function. This makes the WP method appealing in the general framework of the relative risk regression model. First order accuracy of the WP method is established using the counting process approach with a partial likelihood filtration. A simulation …

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The Combination Of Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield Jul 2006

The Combination Of Ecological And Case-Control Data, Sebastien Haneuse, Jon Wakefield

UW Biostatistics Working Paper Series

Ecological studies, in which data are available at the level of the group, rather than at the level of the individual, are susceptible to a range of biases due to their inability to characterize within-group variability in exposures and confounders. In order to overcome these biases, we propose a hybrid design in which ecological data are supplemented with a sample of individual-level case-control data. We develop the likelihood for this design and illustrate its benefits via simulation, both in bias reduction when compared to an ecological study, and in efficiency gains relative to a conventional case-control study. An interesting special …

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On The Potential For Ill-Logic With Logically Defined Outcomes, Xianbin Li, Brian S. Caffo, Daniel O. Scharfstein Jul 2006

On The Potential For Ill-Logic With Logically Defined Outcomes, Xianbin Li, Brian S. Caffo, Daniel O. Scharfstein

Johns Hopkins University, Dept. of Biostatistics Working Papers

Logically defined outcomes are commonly used in medical diagnoses and epidemiological research. When missing values in the original outcomes exist, the method of handling the missingness can have unintended consequences, even if the original outcomes are missing completely at random. Complicating the issue is that the default behavior of standard statistical packages yields different results. In this paper, we consider two binary original outcomes, which are missing completely at random. For estimating the prevalence of a logically defined "or" outcome, we discuss the properties of four estimators: complete case estimator, all-available case estimator, maximum likelihood estimator (MLE), and moment-based estimator. …

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Evaluating Causal Effect Predictiveness Of Candidate Surrogate Endpoints, Peter B. Gilbert, Michael Hudgens Jul 2006

Evaluating Causal Effect Predictiveness Of Candidate Surrogate Endpoints, Peter B. Gilbert, Michael Hudgens

UW Biostatistics Working Paper Series

Most methods for evaluating surrogate endpoints measure validity in terms of net effects (i.e., treatment effects adjusted for the biomarker measured after randomization). Frangakis and Rubin (2002, Biometrics) criticized these approaches because net effects may reflect selection bias, and suggested an alternative definition of a surrogate endpoint (a "principal" surrogate) based on causal effects. For evaluating principal surrogates we introduce a causal effect predictiveness (CEP) surface, which quantifies how well causal treatment effects on the biomarker predict causal treatment effects on the clinical endpoint. The CEP surface is not identifiable in general due to missing potential outcomes. However, by incorporating …

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Causal Comparisons In Randomized Trials Of Two Active Treatments: The Effect Of Supervised Exercise To Promote Smoking Cessation, Jason Roy, Joseph W. Hogan Jul 2006

Causal Comparisons In Randomized Trials Of Two Active Treatments: The Effect Of Supervised Exercise To Promote Smoking Cessation, Jason Roy, Joseph W. Hogan

COBRA Preprint Series

In behavioral medicine trials, such as smoking cessation trials, two or more active treatments are often compared. Noncompliance by some subjects with their assigned treatment poses a challenge to the data analyst. Causal parameters of interest might include those defined by subpopulations based on their potential compliance status under each assignment, using the principal stratification framework (e.g., causal effect of new therapy compared to standard therapy among subjects that would comply with either intervention). Even if subjects in one arm do not have access to the other treatment(s), the causal effect of each treatment typically can only be identified from …

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Erratum: The Emergence Of A Large-Scale Coherent Structure Under Small-Scale Random Bombardments (Communications On Pure And Applied Mathematics (2006) 59:4 (467-500)), Andrew Majda, Xiaoming Wang Jul 2006

Erratum: The Emergence Of A Large-Scale Coherent Structure Under Small-Scale Random Bombardments (Communications On Pure And Applied Mathematics (2006) 59:4 (467-500)), Andrew Majda, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

No abstract provided.

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Algorithms For Sensor Chip Alignment To Blind Datums, Gary B. Hughes Jul 2006

Algorithms For Sensor Chip Alignment To Blind Datums, Gary B. Hughes

Statistics

The sensor element of an imaging system should be mounted into its housing in such a way that the scene can be properly focused onto the sensor element's focal plane over the active area. Operational imaging requirements are forcing increasingly smaller tolerances on sensor alignment, and manufacturing systems must improve alignment capability to keep pace. Imaging system designs include reference datums that provide the basis for manufacturing alignment of optical components in each subassembly. Design constraints for alignment of the sensor element into the camera housing typically include x,y,z, clocking, and parallelism specifications. Measurement of z and parallelism positioning is …

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Estimating Familial Correlations Using A Kotz Type Density, Amal Helu Jul 2006

Estimating Familial Correlations Using A Kotz Type Density, Amal Helu

Mathematics & Statistics Theses & Dissertations

Two useful familial correlations often used to study the resemblance between the family members are the sib-sib correlation (ρss) and the mom-sib or parent-sib correlation (ρps). Since their introduction early in the last century by Galton, Fisher and others, many improved estimators of these correlations have been suggested in the literature. Several moment based estimators as well as the maximum likelihood estimators under the assumption of multivariate normality have been extensively studied and compared by various authors. However, the performance of these estimators when the data are not from multivariate normal distribution is poor. In this …

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